A Dynamic Distribution Model in Cold Supply Chains Using Ant Colony Optimization

In today's competitive world, reducing the distribution costs is an important issue that lies in the forefront of industry managers' thinking. A large percentage of the overall price of a given product belongs to distribution costs. Accordingly, eliminating unnecessary trips and optimizing traversed routes are considered to be one of the ideal solutions to reduce distribution costs. The aim of this study is to develop a dynamic distribution model in cold supply chains of dairy products by using an enhanced hybrid metaheuristic approach based on ant colony optimization. The proposed distribution model is defined according to the capacitated vehicle routing problem (CVRP) where vehicles' routes are not specified for the distribution of dairy products and depending on the volume of orders requested by each trailer on a given day, the minimum number of vehicles along with optimal distribution routes are determined. We assess the efficiency of our proposed distribution model by generating some test data inspired by the data collected from Qazvin Pegah Dairy Company in five different levels of distribution. The evaluation criterion is compare with the results of the current static distribution system. The experimental results indicate that the proposed dynamic distribution model exhibits more efficiency and flexibility than the static distribution system in terms of transportation costs, manpower and handling costs due to fewer number of vehicles employed, shorter mileage traversed and less fuel consumed.